Men in Black: The impact of new contracts on football referees performances

Transcription

1 University of Liverpool From the SelectedWorks of Dr Babatunde Buraimo October 20, 2010 Men in Black: The impact of new contracts on football referees performances Babatunde Buraimo, University of Central Lancashire Alex Bryson Rob Simmons, Lancaster University Available at:

2 Men in Black: The impact of new contracts on football referees performances A L E X B R Y S O N L O N D O N S C H O O L O F E C O N O M I C S B A B A T U N D E B U R A I M O U N I V E R S I T Y O F C E N T R A L L A N C A S H I R E R O B S I M M O N S L A N C A S T E R U N I V E R S I T Y

3 Outline of Presentation Motivation, background and context Sports officials in the spotlight Literature highlights Referees labour market Theoretical analysis Method, data and modelling Results Concluding remarks and policy implications

4 M O T I V A T I O N, B A C K G R O U N D A N D C O N T E X T & S P O R T S O F F I C I A L S I N T H E S P O T L I G H T

5 Motivation, background and context Overwhelming amount of data on decision-making and behaviour Salary contracts have their own incentive effects; not convincingly explored very much in empirical literature Misspecification in previous studies Discourse between reality and perception Improve decision-making

6 Our contribution Identify productivity effects of switch from match fee to salary Exploit panel data on individual We observe referees over time: pre- and post- the switch so can account for fixed unobservable worker attributes We observe workers entering and leaving profession, so can examine the extent to which productivity is driven by referee sorting

7 Referees in the Spotlight

8 FIFA World Cup final: Holland versus Spain

9 Racist officials? Foul calls by referee crew in NBA

10 L I T E R A T U R E H I G H L I G H T S & R E F E R E E S L A B O U R M A R K E T

11 Literature: some highlights Nevill, A., Balmer, N. and Williams, A. (2002) The influence of crowd noise and experience upon refereeing decisions in football, Psychology of Sport and Exercise, 3, Laboratory experiment with crowd noise 15.5% fewer fouls against the home team compared with those watching in silence Garicano, L., Palacios-Huerta, I. and Prendergast, C. (2005) Favoritism under social pressure, Review of Economics and Statistics, 87, When match is not close, no bias Injury time allocated in close match, bias in favour of home team Dohmen, T. (2008) The influence of social forces: evidence from the behavior of football referees, Economic Inquiry, 46, Home teams are systematically awarding more stoppage time in close matches in which they are behind. Home teams are favoured in decisions to award goals and penalty kicks

12 Literature: some highlights Rickman, N. and Witt, R. (2008) Favouritism and financial incentives: a natural experiment, Economica, 75, Length of injury time in close matches Referees exercised favouritism prior to professionalism but not afterwards Buraimo, B., Forrest, D. and Simmons R. (2010) The 12th man?: refereeing bias in English and German soccer. Journal of the Royal Statistical Society: Series A (Statistics in Society), 173, Within-game events (minute-by-minute analysis) Home team favouritism induced by crowd pressure Favourite and underdog status reveals size of home bias

13 Referees labour market Prior to season all paid match fee From Premiership referees paid a salary plus match fee Salaried referees required to undertake regular off-the-job training All Premiership and Championship referees eligible if promoted to the Select group from National group Managed by Professional Game Match Officials Limited (PGMOL)

14 Salaries and Tier 1 match fees after 2001 Income from salaries much higher than match fee and real value increases over time Season Salary Match fee 2001/02 33, /06 50, /08 53, /09 57, Current earnings of around 65,000

15 Number of referees : pre- and contract periods Season Tier 1 only Tier 2 only Tiers 1 and 2 All referees Referees on salaried contracts

16 Mean no. games per season by tier and contract Tier 1 Tier 2 Season Contract Non-contract Contract Non-contract

17 T H E O R E T I C A L A N A L Y S I S & M E T H O D, D A T A A N D M O D E L L I N G

18 Can salary elicit improved performance? Mechanisms Career concerns (incentive) Salary contracts reviewed after 2 seasons (later 1) Efficiency wage effect (higher wages) Quality effect through training Worker sorting

19 Measuring and modelling performance Poor performance readily observable and sanctions immediate Dropped Reputational damage Decisions influenced by fan pressure Controls for local rivals, crowd size Performance comprises 3 elements Training Preventative effort Sanctions (or cards) Cost of preventative effort and training vary by type of contract

20 0 Percent Performance scores by select and national groups Referee score Graphs by Referee on Select Group (Data source: The Times)

21 Impact of sanctions on performance (n = 1305) Performance scores span just to (and not to ) Good referees show fewer cards (Frick et al., 2008) performance f ( sanctions, preventative, training ) performance 0 yellow 1 dismissal β 2 n season γ m referee performance yellow ( 7.87) 0.311dismissal β ( 3.83) n season γ m referee Given relationship between performance and cards Yellow cards and dismissal are good proxies

22 Data Data comprises 11,169 of 11,184 matches played in Tiers 1 and 2 between and All 168 referees officiating those games 9 only tier only tier 2 45 both tier 1 and tier 2 All Tier 1 games officiated by salaried referees from with a few exceptions But 15% of Tier 2 games officiated by salaried referees

23 Methodological approach Natural experiment Difference-in-difference FAPL Match fee FAPL Salaried TIER 1 x POST Championship Match fee Championship Match fee Up until onwards

24 Model Unit of observation: football match Dependent variable: cards per match Empirical model of performance Sanctions = g(tier, attendance, pre and contract periods, derby, score, team performances, period within season, individual referee effect, season, TIER 1 x POST2000-1) Control and FOCUS variables Regression analysis with TIER 1 POST capturing introduction of salaries

25 R E S U L T S & C O N C L U S I O N S A N D P O L I C Y I M P L I C A T I O N S

26 Regression analysis with referee effects for number of yellow cards per game

27 Regression analysis with referee effects for number of dismissals per game

28 Interpretation Impact of salary is a reduction in cards Robust to various model specifications Sanctions being substituted with preventative effort Theoretical and mathematical justification, as well as empirical modelling Career concerns Quality effect through training

29 Conclusions and policy implications Worker performance improves with salary Impact due to Non-random allocation of contracts Worker sorting Remainder due to salary contracts Career concerns, training or income Reallocate resources from... to referees Efficiency improvements

30 References Buraimo, B., Forrest, D. and Simmons R. (2010) The 12th man?: refereeing bias in English and German soccer. Journal of the Royal Statistical Society: Series A (Statistics in Society), 173, Dohmen, T. (2008) The influence of social forces: evidence from the behavior of football referees, Economic Inquiry, 46, Garicano, L., Palacios-Huerta, I. and Prendergast, C. (2005) Favoritism under social pressure, The Review of Economics and Statistics, 87, Nevill, A., Balmer, N. and Williams, A. (2002) The influence of crowd noise and experience upon refereeing decisions in football, Psychology of Sport and Exercise, 3, Rickman, N. and Witt, R. (2008) Favouritism and financial incentives: a natural experiment, Economica, 75,

31 Men in Black T H A N K Y O U C O M M E N T S & Q U E S T I O N S